{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b234248e-10ac-4434-8696-9ea212a99e38",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 建立Neo4j链接"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "420c860e-2474-4b0f-8a47-c26ef0c73f0c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: neo4j in c:\\users\\linqu\\appdata\\roaming\\python\\python310\\site-packages (5.7.0)\n",
      "Requirement already satisfied: pyahocorasick in c:\\users\\linqu\\appdata\\roaming\\python\\python310\\site-packages (2.0.0)\n",
      "Collecting numpy\n",
      "  Downloading numpy-1.25.1-cp310-cp310-win_amd64.whl (15.0 MB)\n",
      "     --------------------------------------- 15.0/15.0 MB 21.1 MB/s eta 0:00:00\n",
      "Requirement already satisfied: pandas in c:\\users\\linqu\\appdata\\roaming\\python\\python310\\site-packages (2.0.0)\n",
      "Requirement already satisfied: pytz in c:\\users\\linqu\\appdata\\roaming\\python\\python310\\site-packages (from neo4j) (2023.3)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\programdata\\miniconda3\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: tzdata>=2022.1 in c:\\users\\linqu\\appdata\\roaming\\python\\python310\\site-packages (from pandas) (2023.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\programdata\\miniconda3\\lib\\site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
      "Installing collected packages: numpy\n",
      "Successfully installed numpy-1.25.1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "tensorflow-intel 2.12.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, which is not installed.\n",
      "tensorboard 2.12.2 requires protobuf>=3.19.6, which is not installed.\n",
      "peft 0.4.0.dev0 requires transformers, which is not installed.\n",
      "flexgen 0.1.7 requires transformers>=4.24, which is not installed.\n",
      "tensorflow-intel 2.12.0 requires numpy<1.24,>=1.22, but you have numpy 1.25.1 which is incompatible.\n"
     ]
    }
   ],
   "source": [
    "!pip install neo4j pyahocorasick numpy pandas --no-warn-script-location"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "966e8d1e-8ecd-47ca-9199-a4231d5717cf",
   "metadata": {},
   "source": [
    "## 定义数据操作对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a4981cfe-10ef-4b5e-9682-9a937f97d2c1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from neo4j_driver import Neo4jConnection, Node"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87b9a714-d27f-489a-904c-31f3624f86cd",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 链接并查看节点数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0432ea5e-e49d-4ce0-af00-506bb9baea73",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = Neo4jConnection('neo4j://localhost:7687/', 'neo4j', 'Lorne@2022')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2bce84ca-29bf-4d21-ae3d-6ae6a224a38d",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.create(Node(\"Person\", name=\"Alice\", age=30))\n",
    "conn.create(Node(\"Person\", name=\"Bob\", age=30))\n",
    "conn.create(Node(\"Person\", name=\"Charlie\", age=30))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a2cdfc34-2779-4875-ac5d-35550e5a100d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据库中的节点总数： 3\n"
     ]
    }
   ],
   "source": [
    "print(\"数据库中的节点总数：\", conn.counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef70f48a-b992-48eb-932f-c8420dc43584",
   "metadata": {},
   "source": [
    "### 创建所有关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5190e175-b4c9-4eab-a812-5ef0aea5dbbc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 创建关系\n",
    "edges = [('Alice', 'Bob'), ('Alice', 'Charlie')]\n",
    "conn.relationship('Person', 'Person', edges, 'KNOWS', 'friend')"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "75dbb4b1-8247-4858-947b-ca944a3fcb10",
   "metadata": {},
   "source": [
    "![image.png](attachment:c963de10-6819-42f2-b388-8c9764e22726.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00b05130-3998-4269-a566-b155bf6ac4f4",
   "metadata": {},
   "source": [
    "## 清空所有的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "458bb730-0592-48fe-8995-007076bfbf21",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "conn.clear()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
